On The Simulation of Northeast Monsoon Rainfall Over Southern Peninsular India in CMIP5 Models

The skill of 34 CMIP5 models to simulate the mean state and interannual variability of Northeast Monsoon Rainfall (NEMR) is studied here. The mean (1979-2005) NEMR over southern Peninsular India (SPIRF), Indian Ocean and Maritime continents (10°S-30°N,40°E- 120°E) is simulated reasonably well by CMIP5 models with pattern correlation ranges from 0.6 to 0.93. Diverse behaviour in the simulation of Indian and Pacific Ocean SST is observed in the CMIP5 models. A set of models (high skill models: HSM), which shows a Negative Indian Ocean Dipole (NIOD) like mean (1979-2005) SST bias in Indian Ocean and strong La Nina like mean SST bias in the Pacific Ocean, are able to simulate the mean NEMR more realistically. Another set of models (low skill models: LSM) which shows a Positive IOD (PIOD) like mean SST bias in the Indian Ocean and weak La Nina like mean SST bias in the Pacific Ocean are not able to simulate the observed equatorial Indian Ocean westerlies, which leads to an abnormal ascending motion and unrealistic wet bias over the western Indian Ocean and dry bias over the southern Peninsular India, southeast Asia and southeast Indian Ocean. The observation analysis reveals that the establishment of South China Sea anticyclone and Bay of Bengal anticyclone during El Nino and PIOD are strongly related with the ascending motion over south peninsular India and enhances the south Peninsular Indian rainfall during NEM season. Around 70% of the CMIP5 models were not able to capture the observed positive correlation that exist between SPIRF and Nino3.4 SST as well as SPIRF and DMI. Unrealistic westward extension of South China Sea anticyclone and Bay of Bengal anticyclone (up to 70°E) in the low skill models (LSM-IAV) manifested as the abnormal descending anomalies and unrealistic dry bias over the southern Peninsular India. This leads to a negative Correlation coefficient (CC) between SPIRF and Nino 3.4 SST as well as SPIRF and DMI in the low skill models. The descending anomalies over South China Sea and ascending anomalies over the western Indian Ocean and southern Peninsular India (50°E-80°E) is well captured but with lower intensity in the high skill models (HSM-IAV) and hence it captures the observed positive CC between SPIRF and Nino3.4 SST as well as SPIRF and DMI.

Spatiotemporal Trend Analysis of Temperature and Rainfall over Ziway Lake Basin, Ethiopia

Rainfall and temperature trends detection is vital for water resources management and decision support systems in agro-hydrology. This study assessed the historical (1983–2005) and future (2026–2100) rainfall, maximum temperature (Tmax), and minimum temperature (Tmin) trends of the Ziway Lake Basin (Ethiopia). The daily observed rainfall and temperature data at eleven stations were obtained from the National Meteorological Agency (NMA) of Ethiopia, while simulated historical and future climate data were obtained from the Coupled Model Intercomparison Project 5 (CMIP5) datasets under Representative Concentration Pathways (RCP) of 4.5 and 8.5. The CMIP5 datasets were statistically downscaled by using the climate model data for hydrologic modeling (CMhyd) tool and bias corrected using the distribution mapping method available in the CMhyd tool. The performance of simulated rainfall, Tmax, and Tmin of the CMIP5 models were statistically evaluated using observation datasets at eleven stations. The results showed that the selected CMIP5 models can reasonably simulate the monthly rainfall, Tmax, and Tmin at the majority of the stations. Modified Mann–Kendall trend test were applied to estimate the trends of annual rainfall, Tmax, and Tmin in the historical and future periods. We found that rainfall experienced no clear trends, while Tmax, and Tmin showed consistently significant increasing trends under both RCP 4.5 and 8.5 scenarios. However, the warming is expected to be greater under RCP 8.5 than RCP 4.5 by the end of the 21st century, resulting in an increasing trend of Tmax and Tmin at all stations. The greatest warming occurred in the central part of the basin, with statistically significant increases largely seen by the end of the 21st century, which is expected to exacerbate the evapotranspiration demand of the area that could negatively affect the freshwater availability within the basin. This study increases our understanding of historic trends and projected future change effects on rainfall- and evapotranspiration-related climate variables, which can be used to inform adaptive water resource management strategies.

Future Projection of Drought Vulnerability over Northeast Provinces of Iran during 2021–2100

Future projection of drought vulnerability is vital for northern provinces of Iran, including North Khorasan, Khorasan-Razavi, and South Khorasan, due to the highly dependent of their economy on agriculture. The study is motivated by the fact that no research has been conducted to project the future Drought Vulnerability Index (DVI). DVI consist of three components of exposure, sensitivity, and adaptation capacity. More exposure levels of drought, higher sensitivity value, and lower adaptation capacity lead to a higher amount of vulnerability. Combined ERA-Interim-observation meteorological data, CMIP5 models under RCP4.5 and RCP8.5 scenarios, and national census data are used to estimate DVI in the past and future periods. CanESM2, GFDL-ESM2M, and CNRM-CM5 General Circulation Model (GCM) are selected from CMIP5 based on Taylor diagram results. The delta-change technique was selected for statistical downscaling of GCM outputs because it is most widely used. The study period is regarded as 1986–2005 as observation and four future 20-years periods during 2021–2100. Results indicated that the dissipation of the class of “very low” vulnerability is eminent in the near future period of 2021–2040 under the RCP4.5 scenario, and all provinces would experience a new worse class of “very high” vulnerability at 2081–2100, both under RCP4.5 and RCP8.5 scenarios.

Objective Identification and Characterisation of Pacific ITCZs in ERA5 and CMIP5 models and their representation in RCMs

<p>The Intertropical Convergence Zone (ITCZ) is recognised as the most crucial feature of the tropical climate producing more than 30% of the global precipitation. Its variability dramatically affects the people living in tropical areas. In the eastern Pacific, a pair of ITCZ, one at each side of the equator, during the boreal spring is evident. It is known as the Double Intertropical Convergence Zone (DITCZ). Generally, the ITCZ in the Pacific is located in the Northern Hemisphere (NH); however, during extreme El Niño events, it can cross the equator, or a wide band of deep convection extending over both hemispheres is to be observed. The DITCZ exists more frequently and with much more strength in General Circulation Models (GCMs), resulting in a spurious bias. The DITCZ bias has been a long-standing tropical bias in climate model simulations since the early beginning. Despite the intense research on the tropical climate and its features, fewer studies investigated the state of the ITCZs through an objective and automated algorithm. Also, much fewer studies have applied such an algorithm to the GCMs output. Unfortunately, far too little attention has been paid to examining how DITCZ bias is transmitted to Regional Climate Models (RCMs). Furthermore, the input variables to the RCM from GCM are prognostic such as wind, temperature and humidity. Since precipitation is not an input, it would be interesting to examine how the representation of ITCZs in the GCMs is unfolded in the RCMs. The method adopted in this study depends on an objective and automated algorithm developed and modified by earlier studies. The algorithm uses layer- and time-averaged winds in the lower troposphere (seven layers between 1000 and 850 hPa), in addition to wet-blub potential temperature, to automatically detect the centre latitude of the ITCZs. Furthermore, it uses GPCP or CMIP5 model precipitation to obtain the extents (i.e. boundaries) of the ITCZs and the precipitation intensities. From reanalysis datasets, the NH ITCZs are found near 8°N, while the Southern Hemisphere (SH) ITCZs are near 5°S. In CMIP5 models, the DITCZ is much stronger and more frequent, and it occurs year-round. Generally, the NH ITCZs are located between 8°N and 10°N while the SH ITCZs are located between 5°S and 10°S. Moreover, models overestimate the tropical precipitation mainly, the centre and full ITCZ intensities. Furthermore, it indicates more vigorous convection in the NH ITCZs than in the SH ITCZs. The study also found that the state of ITCZ in GCMs directly influences the bias in RCM monthly precipitation. However, it depends mainly on the RCM employed. The most affected nations by DITCZ bias are Ecuador and Peru. Quantitative in-depth analysis of precipitation of GCMs and RCMs is still <span>on</span>going.</p>

Early-winter North Atlantic low-level jet latitude biases in climate models: implications for simulated regional atmosphere-ocean linkages

Climate model biases in the North Atlantic (NA) low-level tropospheric westerly jet are a major impediment to reliably representing variability of the NA climate system and its wider influence, in particular over western Europe. A major aspect of the biases is the occurrence of a prominent early-winter equatorward jet bias in Coupled Model Inter-comparison Project Phase 5 (CMIP5) models that has implications for NA atmosphere-ocean coupling. Here we assess whether this bias is reduced in the new CMIP6 models and assess implications for model representation of NA atmosphere-ocean linkages, in particular over the sub-polar gyre (SPG) region. Historical simulations from the CMIP5 and CMIP6 model datasets were compared against reanalysis data over the period 1862-2005. The results show that the early-winter equatorward bias remains present in CMIP6 models, although with an approximately one-fifth reduction compared to CMIP5. The equatorward bias is mainly associated with a weaker-than-observed frequency of poleward excursions of the jet to its northern position. A potential explanation is provided through the identification of a strong link between NA jet latitude bias and systematically too-weak model-simulated low-level baroclinicity over eastern North America in early-winter. CMIP models with larger equatorward jet biases exhibit weaker correlation between temporal variability in speed of the jet and sea surface conditions (sea surface temperatures and turbulent heat fluxes) over the SPG. The results imply that the early-winter equatorward bias in jet latitude in CMIP models could partially explain other known biases, such as the weaker-than-observed seasonal-decadal predictability of the NA climate system.

A Cloudier Picture of Ice-Albedo Feedback in CMIP6 Models

Increased solar absorption is an important driver of Arctic Amplification, the interconnected set of processes and feedbacks by which Arctic temperatures respond more rapidly than global temperatures to climate forcing. The amount of sunlight absorbed in the Arctic is strongly modulated by seasonal ice and snow cover. Sea ice declines and shorter periods of seasonal snow cover in recent decades have increased solar absorption, amplifying local warming relative to the planet as a whole. However, this Arctic albedo feedback would be substantially larger in the absence of the ubiquitous cloud cover that exists throughout the region. Clouds have been observed to mask the effects of reduced surface albedo and slow the emergence of secular trends in net solar absorption. Applying analogous metrics to several models from the 6th Climate Model Intercomparison Project (CMIP6), we find that ambiguity in the influence of clouds on predicted Arctic solar absorption trends has increased relative to the previous generation of climate models despite better agreement with the observed albedo sensitivity to sea ice variations. Arctic albedo responses to sea ice loss are stronger in CMIP6 than in CMIP5 in all summer months. This agrees better with observations, but models still slightly underestimate albedo sensitivity to sea ice changes relative to observations. Never-the-less, nearly all CMIP6 models predict that the Arctic is now absorbing more solar radiation than at the start of the century, consistent with recent observations. In fact, many CMIP6 models simulate trends that are too strong relative to internal variability, and spread in predicted Arctic albedo changes has increased since CMIP5. This increased uncertainty can be traced to increased ambiguity in how clouds influence natural and forced variations in Arctic solar absorption. While nearly all CMIP5 models agreed with observations that clouds delay the emergence of forced trends, about half of CMIP6 models suggest that clouds accelerate their emergence from natural variability. Isolating atmospheric contributions to total Arctic reflection suggests that this diverging behavior may be linked to stronger Arctic cloud feedbacks in the latest generation of climate models.

The Potential Mechanisms of AMOC Multidecadal Periods in CMIP6/CMIP5 Preindustrial Simulations

Observations, theoretical analyses, and climate models show that the period of multidecadal variability of the Atlantic Meridional Overturning Circulation (AMOC) is related to westward temperature propagations in the subpolar North Atlantic, which is modulated by oceanic baroclinic Rossby waves. Here, we find major periods of AMOC variability of 12-28 years and associated westward temperature propagations in the preindustrial simulations of 9 CMIP6/CMIP5 models. Comparison with observations shows that the models reasonably simulate ocean stratifications in turn oceanic Rossby waves in the subpolar North Atlantic. The timescales of Rossby waves propagating on a static background flow across the subpolar North Atlantic basin overestimate the AMOC periods. The mean flow effects involving westward geostrophic self-advection and eastward mean advection largely shorten and greatly improve the estimate of AMOC periods through increasing Rossby wave speeds. Our results illustrate the importance of considering mean flow effects on Rossby wave propagations in the estimate of AMOC periods.

Relationship between Southern Hemispheric jet variability and forced response: the role of the stratosphere

Climate models show a wide range of Southern Hemispheric jet responses to greenhouse gas forcing. One approach to constrain future jet response is by utilising the fluctuation-dissipation theorem (FDT) that links forced response to internal variability timescales, with the Southern Annular Mode (SAM) the most dominant mode of variability of the Southern Hemispheric jet. We show that stratospheric variability approximately doubles the SAM timescale during austral summer in both re-analysis data and models from the Coupled Model Intercomparison Project, phase 5 (CMIP5). Using a simple barotropic model, we demonstrate how the enhanced SAM timescale subsequently leads to an overestimate of the forced jet response based on FDT, and introduce a method to correct for the stratospheric influence. Even after accounting for this influence, the SAM timescale cannot explain inter-model differences in the forced jet shift across CMIP5 models during austral summer, owing to other confounding factors.

MJO propagation over the Indian Ocean and Western Pacific in CMIP5 Models: Roles of Background States

This study explored the impacts of background states on the propagation of the Madden-Julian Oscillation (MJO) in 24 CMIP5 models using a precipitation-based MJO tracking method. The ability of the model to reproduce the MJO propagation is reflected in the occurrence frequency of individual MJO events. Moisture budget analysis suggests that the occurrence frequencies of MJO events that propagate across the Indian Ocean (IO-MJO) and western Pacific (WP-MJO) in the models are mainly related to the low-level meridional moisture advection ahead of the MJO convection center. This advection is tightly associated with the background distribution of low-level moisture. Drier biases in background low-level moisture over the entire tropical regions account for underestimated MJO occurrence frequency in the bottom-tier simulations. This study highlights the importance of reproducing the year-to-year background states for the simulations of MJO propagation in the models by further decomposing the background states into the climatology and anomaly components. The background meridional moisture gradient account for the IO-MJO occurrence frequency is closely related to its climatology component, however, the anomaly component regulated by the El Niño–Southern Oscillation (ENSO) is also important for the WP-MJO occurrence frequency. The year-to-year variations of background zonal and meridional gradients associated with ENSO account for the IO-MJO occurrence frequency tend to be offset with each other. As a result, the ENSO shows no significant impact on the IO-MJO occurrence frequency. However, the MJO events tend to more likely propagate across the western Pacific during El Niño years.