Sensitivity of Caspian sea‐ice to air temperature

Tamura‐Wicks, Helen; Toumi, Ralf; Budgell, W. Paul

doi:10.1002/qj.2592

Cited by 9 publications

(6 citation statements)

References 49 publications

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“…Therefore, in the northern portion of the CS, heat fluxes from the lake surface into the atmosphere tend to be overestimated in winter. Under warmer climate conditions, when winter lake ice disappears (Tamura‐Wicks et al., 2015), this model bias would also vanish. Hence, the importance of winter lake ice effects depends on the background climate.…”

Section: Discussionmentioning

confidence: 99%

Impacts of Variations in Caspian Sea Surface Area on Catchment‐Scale and Large‐Scale Climate

et al. 2021

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The Caspian Sea (CS) is the largest inland lake in the world. Large variations in sea level and surface area occurred in the past and are projected for the future. The potential impacts on regional and large-scale hydroclimate are not well understood. Here, we examine the impact of CS area on climate within its catchment and across the northern hemisphere, for the first time with a fully coupled climate model. The Community Earth System Model (CESM1.2.2) is used to simulate the climate of four scenarios: (a) larger than present CS area, (b) current area, (c) smaller than present area, and (d) no-CS scenario. The results reveal large changes in the regional atmospheric water budget. Evaporation (e) over the sea increases with increasing area, while precipitation (P) increases over the south-west CS with increasing area. P-E over the CS catchment decreases as CS surface area increases, indicating a dominant negative lake-evaporation feedback. A larger CS reduces summer surface air temperatures and increases winter temperatures. The impacts extend eastwards, where summer precipitation is enhanced over central Asia and the north-western Pacific experiences warming with reduced winter sea ice. Our results also indicate weakening of the 500-hPa troughs over the northern Pacific with larger CS area. We find a thermal response triggers a southward shift of the upper troposphere jet stream during summer. Our findings establish that changing CS area results in climate impacts of such scope that CS area variations should be incorporated into climate model simulations, including palaeo and future scenarios. Plain Language SummaryThe Caspian Sea is the largest land-locked water body in the world. It is filled by rivers draining a vast region from northern Russia to Iran. The size of the Caspian Sea has varied considerably over recent centuries and millennia due to various factors, including changes in climate. Conversely, as the area of the sea changes it also has impacts on the climate, but there are significant questions about how and where those impacts would be felt. In this study we used a stateof-the-art climate model in which we specified different sizes of Caspian Sea in order to examine how the climate changes as its area increases. We observed that the local seasonal cycle of temperatures gets smaller, and evaporation increases, while there are more spatially complex changes in local rainfall. Furthermore, the impacts on atmospheric circulation occur as far as the north Pacific, with resulting increases in temperature and decreases in sea-ice coverage in winter as the Caspian area increases. The climate impacts are so significant and geographically extensive that climate models used to simulate climate change (both in future and past scenarios) should incorporate changes to the Caspian Sea area if they are to robustly model regional climate. KORICHE ET AL.

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Section: Discussionmentioning

confidence: 99%

Impacts of Variations in Caspian Sea Surface Area on Catchment‐Scale and Large‐Scale Climate

et al. 2021

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“…Sea ice formation is strongly related to the period of surface air temperature remaining below or above the freezing/melting point of the seawater, which can be quantified by CFDD and CMDD, respectively [5,14,58]. The mathematical definitions of the two meteorological parameters are as follows:…”

Section: Meteorological Parametersmentioning

confidence: 99%

Monitoring the Characteristics of the Bohai Sea Ice Using High-Resolution Geostationary Ocean Color Imager (GOCI) Data

Huang

Shao

et al. 2019

Sustainability

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Satellite remote sensing data, such as moderate resolution imaging spectroradiometers (MODIS) and advanced very high-resolution radiometers (AVHRR), are being widely used to monitor sea ice conditions and their variability in the Bohai Sea, the southernmost frozen sea in the Northern Hemisphere. Monitoring the characteristics of the Bohai Sea ice can provide crucial information for ice disaster prevention for marine transportation, oil field operation, and regional climate change studies. Although these satellite data cover the study area with fairly high spatial resolution, their typically limited cloudless images pose serious restrictions for continuous observation of short-term dynamics, such as sub-seasonal changes. In this study, high spatiotemporal resolution (500 m and eight images per day) geostationary ocean color imager (GOCI) data with a high proportion of cloud-free images were used to monitor the characteristics of the Bohai Sea ice, including area and thickness. An object-based feature extraction method and an albedo-based thickness inversion model were used for estimating sea ice area and thickness, respectively. To demonstrate the efficacy of the new dataset, a total of 68 GOCI images were selected to analyze the evolution of sea ice area and thickness during the winter of 2012–2013 with severe sea ice conditions. The extracted sea ice area was validated using Landsat Thematic Mapper (TM) data with higher spatial resolution, and the estimated sea ice thickness was found to be consistent with in situ observation results. The entire sea ice freezing–melting processes, including the key events such as the day with the maximum ice area and the first and last days of the frozen season, were better resolved by the high temporal-resolution GOCI data compared with MODIS or AVHRR data. Both characteristics were found to be closely correlated with cumulative freezing/melting degree days. Our study demonstrates the applicability of the GOCI data as an improved dataset for studying the Bohai Sea ice, particularly for purposes that require high temporal resolution data, such as sea ice disaster monitoring.

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“…During the winter (from mid-November to mid-March), sea ice cover develops and extends in the N CS with some strong spatial variability from one year to another (Kouraev et al, 2004). Linking ice conditions to air temperatures in the N CS, Tamura-Wicks et al (2015) showed critical temperatures required for ice formation and suggested that the N CS could be ice-free by 2100. We investigate in the present work the impact of high resolution atmospheric forcing on the dynamic of the Caspian Sea.…”

Section: Introductionmentioning

confidence: 99%

A fully-coupled atmosphere-ocean-wave model of the Caspian Sea

Bruneau

Toumi

2016

Ocean Modelling

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Located in the mid-latitudes, the Caspian Sea is the largest enclosed basin in the world. A fully-coupled atmosphere-ocean-wave model of the Caspian Sea at high resolution (8km) for a period of three years is presented. After validating each component of the modelling platform, the wave state of the Caspian Sea is studied. Results show very different wave regimes between the three different basins, a strong seasonality and an almost swell-free state.It is shown here that waves modify the horizontal eddy viscosity and vertical heat diffusion. However, due to a reasonably weak annual wave state, these effects are restricted to the upper-ocean layer (< 30 m) except during the most severe events (100 m).

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Sensitivity of Caspian sea‐ice to air temperature

Cited by 9 publications

References 49 publications

Impacts of Variations in Caspian Sea Surface Area on Catchment‐Scale and Large‐Scale Climate

Impacts of Variations in Caspian Sea Surface Area on Catchment‐Scale and Large‐Scale Climate

Monitoring the Characteristics of the Bohai Sea Ice Using High-Resolution Geostationary Ocean Color Imager (GOCI) Data

A fully-coupled atmosphere-ocean-wave model of the Caspian Sea

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