The curious case of a strong relationship between ENSO and Indian summer monsoon in CFSv2 model
- Priyanshi Singhai a b c, Arindam Chakraborty a b, Kaushik Jana d, Kavirajan Rajendran e f, Sajani Surendran f, Kathy Pegion ca Centre for Atmospheric and Oceanic Sciences, Indian Institute of Science, CV Raman Rd, Bengaluru, 560012, Karnataka, India
b Divecha Centre for Climate Change, Indian Institute of Science, CV Raman Rd, Bengaluru, 560012, Karnataka, India
c School of Meteorology, University of Oklahoma, 120 David L Boren Blvd, Norman, 73072, OK, USA
d Mathematical and Physical Sciences Division, Ahmedabad University, Commerce Six Roads, Naranpark Society, Navrangpura, Ahmedabad, 380009, Gujarat, India
e Kerala State Council for Science, Technology and Environment (KSCSTE), Institute for Climate Change Studies (KSCSTE-ICCS), Deepthi Nagar Road Kanjikuzhi, Kottayam, 686004, Kerala, India
f CSIR Fourth Paradigm Institute (CSIR-4PI), NAL Belur Campus Wind Tunnel Road, Bengaluru, 560037, Karnataka, India
Abstract
An ensemble of forecasts is necessary to identify the uncertainty in predicting a non-linear system like climate. While ensemble averages are often used to represent the mean state and diagnose physical mechanisms, they can lead to information loss and inaccurate assessment of the model’s characteristics. Here, we highlight an intriguing case in the seasonal hindcasts of the Climate Forecast System version 2 (CFSv2). While all ensemble members often agree on the sign of predicted El Niño Southern Oscillation (ENSO) for a particular season, non-ENSO climate forcings, although present in some of the individual members, are disparate. As a result, an ensemble mean retains ENSO anomalies while diminishing non-ENSO signals. This difference between ENSO and non-ENSO signals significantly influences moisture convergence and Indian summer monsoon rainfall (ISMR). This stronger influence of ENSO on seasonal predictions increases ENSO–ISMR correlation in ensemble mean seasonal hindcasts. Thus, this discrepancy in the ENSO–ISMR relationship is not present in the individual ensemble members, considered individually or together (without averaging) as independent realizations. Therefore, adequate care should be taken while evaluating physical mechanisms of teleconnection in ensemble mean predictions that can often be skewed due to constructive or destructive superposition of different impacts.
Shifts in bioclimatic zones mirror climate change signals in a tropical agriculture-dominated Bharathapuzha River basin of southern Western Ghats (India)
-Sinan Nizara, Jobin Thomasb, P. J. Jainetc d, Dawn Emil Sebastiane, U. Surendranc f, Balaji Narasimhang, K. P. Sudheerg h ia KSCSTE-Institute for Climate Change Studies, Kottayam, India
b Department of Geology and Geological Engineering, University of Mississippi, Oxford, Mississippi, USA
c KSCSTE-Centre for Water Resources Development and Management, Calicut, India
d Department of Civil Engineering, Indian Institute of Technology Palakkad, Palakkad, India
e School of Environment and Sustainability, Indian Institute for Human Settlements, Bengaluru, India
f ICAR-National Bureau of Soil Survey and Land Use Planning, Nagpur, India
g Department of Civil Engineering, Indian Institute of Technology Madras, Chennai, India
h Department of Agricultural and Biological Engineering, Purdue University, West Lafayette, Indiana, USA
i Kerala State Council for Science Technology and Environment, Thiruvananthapuram, India
Abstract
Assessing anthropogenic climate change in a regional context is challenging due to the spatial heterogeneity of climatic variables and is more complicated than at the global scale. Especially in the Tropics, such spatial variations are expected to increase, warranting the identification of homogeneous climatic zones for assessing regional climate change. The present study explores the ability of bioclimatic variables in defining regional climatic zones, and the detection of climate change therein. We hypothesize that the identification of homogeneous climatic zones based on bioclimatic variables could be an effective approach rather than the conventional extreme climate-based indices to identify climate change signals. To demonstrate the hypothesis, bioclimatic variables representing the generalized climatic characteristics of a tropical river basin were derived from observed gridded datasets of rainfall and temperature. Clusters of homogeneous climatic zones were identified, and their temporal variations were analysed to examine the existence of climate change. The results indicate that despite the spatial heterogeneity in extreme climate-based indices, the bioclimatic variables-based approach renders a meaningful representation of the regional climatic pattern. Investigation of bioclimatic zones of the study area helped to identify a shift in its climatic zones with a slant towards drier conditions. Further, future changes in climatic zones were identified from 13 different GCMs that participated in the CMIP6, projecting drier conditions over the basin, with varying spatial extend based on future emission scenarios. The study significantly contributes towards the identification of climatologically fragile regions in changing climate, which is an essential component in developing any regional climate change adaptation and mitigation strategy.
Evolution of Antarctic Sea Ice Ahead of the Record Low Annual Maximum Extent in September 2023
-Babula Jenaa, S. Kshitijaa, C. C. Bajishb, John Turnerc, Caroline Holmesc, Jeremy Wilkinsonc, Rahul Mohana, M. Thambanaa National Centre for Polar and Ocean Research, Ministry of Earth Sciences, Vasco da Gama, India
b KSCSTE-Institute for Climate Change Studies, Kottayam, India
c British Antarctic Survey, Natural Environment Research Council, Cambridge, UK
Abstract
The 2023 Antarctic sea ice extent (SIE) maximum on 7 September was the lowest annual maximum in the satellite era (16.98 × 106 km2), with the largest contributions to the anomaly coming from the Ross (37.7%, −0.57 × 106 km2) and Weddell (32.9%, −0.49 × 106 km2) Seas. The SIE was low due to anomalously warm (>0.3°C) upper-ocean temperatures combined with anomalously strong northerly winds impeding the ice advance during the fall and winter. Northerly winds of >12 ms−1 in the Weddell Sea occurred because of negative pressure anomalies over the Antarctic Peninsula, while those in the Ross Sea were associated with extreme blocking episodes off the Ross Ice Shelf. The Ross Sea experienced an unprecedented SIE decrease of −1.08 × 103 km2 d−1 from 1 June till the annual maximum. The passage of quasi-stationary and explosive polar cyclones contributed to periods of southward ice-edge shift in both sectors.
Occurrence of an unusual extensive ice-free feature within the pack ice of the central Weddell Sea, Antarctica
a National Centre for Polar and Ocean Research, Ministry of Earth Sciences, Goa, India
b British Antarctic Survey, Natural Environment Research Council, Cambridge, UK
c KSCSTE - Institute for Climate Change Studies, Kottayam, India
d Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China
Abstract
We investigate an unusual extensive ice-free feature (EIF) within the pack ice that developed in the central Weddell Sea in December 1980 on the edge of the multi-year sea ice off the east coast of the Antarctic Peninsula. The EIF was first apparent on satellite imagery on 8 December 1980 and expanded until it reached its largest areal extent of ~5.4 × 105 km2 on 26 December. The combined influences of near-record strength ( ~ 15 ms−1) cold winds from the Antarctic continent (transporting sea ice northward and creating an area of thin ice), increased shortwave radiation and net heat flux into the ocean, passage of deep polar storms, and the upwelling of high saline warm water led to the opening of this unique EIF. It is still the largest ice-free feature within the pack ice resembling a polynya observed in the central Weddell Sea during the satellite era, contributing significantly to the 1981 Weddell Sea sea ice extent minimum of 0.793 × 106 km2, the lowest on record. The development mechanism of this EIF was different from the 1970’s Weddell open ocean polynya which occurred within the winter sea ice cover through enhanced ocean convection.
Effect of crop management practices on water balance components in an agricultural catchment
-Jose George, Sinan Nizar, Gowri R, Aiswarya B. Babu, C. C. Bajish and K. P. Sudheer
Isopluvial Maps of Kerala using IMD Gridded Rainfall Data
-Aiswarya P Babu, Sinan Nizar, D S Pai
Spatio-Temporal Distribution of Aerosols Over Kerala: A SatelliteBased Assessment in Polluting Climate
-Sruthin Vijay, Sinan Nizar, D S Pai
Kerala Climate Statement 2023
Kerala Climate Statement 2022
Kerala Climate Statement 2021