The influence of the Laurentian Great Lakes on climate is assessed by comparing two decade-long simulations, with the lakes either included or excluded, using the Abdus Salam International Centre for Theoretical Physics Regional Climate Model, version 4. The Great Lakes dampen the variability in near-surface air temperature across the surrounding region while reducing the amplitude of the diurnal cycle and annual cycle of air temperature. The impacts of the Great Lakes on the regional surface energy budget include an increase (decrease) in turbulent fluxes during the cold (warm) season and an increase in surface downward shortwave radiation flux during summer due to diminished atmospheric moisture and convective cloud amount. Changes in the hydrologic budget due to the presence of the Great Lakes include increases in evaporation and precipitation during October–March and decreases during May–August, along with springtime reductions in snowmelt-related runoff. Circulation responses consist of a regionwide decrease in sea level pressure in autumn–winter and an increase in summer, with enhanced ascent and descent in the two seasons, respectively. The most pronounced simulated impact of the Great Lakes on synoptic systems traversing the basin is a weakening of cold-season anticyclones.

A historical simulation (1976–2002) of the Abdus Salam International Centre for Theoretical Physics Regional Climate Model, version 4 (ICTP RegCM4), coupled to a one-dimensional lake model, is validated against observed lake ice cover and snowfall across the Great Lakes Basin. The model reproduces the broad temporal and spatial features of both variables in terms of spatial distribution, seasonal cycle, and interannual variability, including climatological characteristics of lake-effect snowfall, although the simulated ice cover is overly extensive largely due to the absence of lake circulations. A definition is introduced for identifying heavy lake-effect snowstorms in regional climate model output for all grid cells in the Great Lakes Basin, using criteria based on location, wind direction, lake ice cover, and snowfall. Simulated heavy lake-effect snowstorms occur most frequently downwind of the Great Lakes, particularly to the east of Lake Ontario and to the east and south of Lake Superior, and are most frequent in December–January. The mechanism for these events is attributed to an anticyclone over the central United States and related cold-air outbreak for areas downwind of Lakes Ontario and Erie, in contrast to a nearby cyclone over the Great Lakes Basin and associated cold front for areas downwind of Lakes Superior, Huron, and Michigan.

Meteorological drought is a natural hazard that can occur under all climatic regimes. Monitoring the drought is a vital and important part of predicting and analyzing drought impacts. Because no single index can represent all facets of meteorological drought, we took a multi-index approach for drought monitoring in this study. We assessed the ability of eight precipitation-based drought indices (SPI (Standardized Precipitation Index), PNI (Percent of Normal Index), DI (Deciles index), EDI (Effective drought index), CZI (China-Z index), MCZI (Modified CZI), RAI (Rainfall Anomaly Index), and ZSI (Z-score Index)) calculated from the station-observed precipitation data and the AgMERRA gridded precipitation data to assess historical drought events during the period 1987-2010 for the Kashafrood Basin of Iran. We also presented the Degree of Dryness Index (DDI) for comparing the intensities of different drought categories in each year of the study period (1987-2010). In general, the correlations among drought indices calculated from the AgMERRA precipitation data were higher than those derived from the station-observed precipitation data. All indices indicated the most severe droughts for the study period occurred in 2001 and 2008. Regardless of data input source, SPI, PNI, and DI were highly inter-correlated (R 2 =0.99). Furthermore, the higher correlations (R 2 =0.99) were also found between CZI and MCZI, and between ZSI and RAI. All indices were able to track drought intensity, but EDI and RAI showed higher DDI values compared with the other indices. Based on the strong correlation among drought indices derived from the AgMERRA precipitation data and from the station-observed precipitation data, we suggest that the AgMERRA precipitation data can be accepted to fill the gaps existed in the station-observed precipitation data in future studies in Iran. In addition, if tested by station-observed precipitation data, the AgMERRA precipitation data may be used for the data-lacking areas.

A 20-km regional climate model, the Abdus Salam International Centre for Theoretical Physics Regional Climate Model version 4 (ICTP RegCM4), is employed to investigate heavy lake-effect snowfall (HLES) over the Great Lakes Basin and the role of ice cover in regulating these events. When coupled to a lake model and driven with atmospheric reanalysis data between 1976 and 2002, RegCM4 reproduces the major characteristics of HLES. The influence of lake ice cover on HLES is investigated through 10 case studies (2 per Great Lake), in which a simulated heavy lake-effect event is compared with a companion simulation having 100% ice cover imposed on one or all of the Great Lakes. These experiments quantify the impact of ice cover on downstream snowfall and demonstrate that Lake Superior has the strongest, most widespread influence on heavy snowfall and Lake Ontario the least. Ice cover strongly affects a wide range of atmospheric variables above and downstream of lakes during HLES, including snowfall, surface energy fluxes, wind speed, temperature, moisture, clouds, and air pressure. Averaged among the 10 events, complete ice coverage causes major reductions in lake-effect snowfall (>80%) and turbulent heat fluxes over the lakes (>90%), less low cloudiness, lower temperatures, and higher air pressure. Another important consequence is a consistent weakening (30%–40%) of lower-tropospheric winds over the lakes when completely frozen. This momentum reduction further decreases over-lake evaporation and weakens downstream wind convergence, thus mitigating lake-effect snowfall. This finding suggests a secondary, dynamical mechanism by which ice cover affects downstream snowfall during HLES events, in addition to the more widely recognized thermodynamic influence.

The National Centers for Environmental Prediction‐National Center for Atmospheric Research (NCEP‐NCAR) monthly mean reanalysis dataset has been used to analyze spatial variations of summertime subtropical anticyclones over the Asia–Africa region. The geopotential height and zonal wind components of 1000, 500, 200, and 100 hPa in a 30‐year period (1971–2000) have been used to determine the spatial and temporal variations of the anticyclone centres, their monthly frequency and latitudinal axis variations during April–October. The results revealed that there is a clear difference in the location of the summer anticyclone centres in lower, middle and upper levels of the troposphere. In the lower levels, the Azores subtropical anticyclone is located at the east of North Atlantic. In the middle levels, the frequencies of anticyclone centre are concentrated over the northwest of Africa, Arabian Peninsula and Iranian Plateau. In the upper troposphere, the geographical location of the anticyclone centres and their frequencies in the summer season exhibit a scattered pattern from south of China up to western Iran at 200 hPa, and a bimodal pattern over the Tibetan and the Iranian Plateaus at 100 hPa. In fact, in the entire study domain, the Iranian Plateau is a preferable location of the middle and upper troposphere anticyclones. The highest observed latitude of the subtropical anticyclone at 100, 200 and 500 hPa levels have been seen over north of Tibetan plateau, a large area from east to west of Asia and Iran during August, July–August and July, respectively. The maximum monthly variation in the latitude of the ridgeline is seen at 500, 200, and 100 hPa from June to July which goes even up to 10 degrees at some longitudes. Copyright © 2009 Royal Meteorological Society

[1] Lake Superior, the northern-most of the Laurentian Great Lakes, is the largest (by surface area) freshwater lake on the planet. Due in part to its high water surface to land area ratio, over one-third of the Lake Superior basin water budget is derived from precipitation falling directly on the lake surface. For most of the Great Lakes (including Lake Superior), historical precipitation estimates extend back to the early 1880s, and are based primarily on land-based gauge measurements. While alternatives to gauge-based estimates have been explored, there is no clear history of applying regional climate models (RCMs) to improve historical over-lake precipitation estimates. To address this gap in regional research, and to advance the state-of-the-art in Great Lakes regional hydrological modeling, we compare 21 years of output from an RCM to conventional gauge-based precipitation estimates for the same time period over the Lake Superior basin. We find that the RCM, unlike the gauge-based method, simulates realistic variations in over-lake atmospheric stability, which propagate into basin-wide precipitation estimates with a relatively low over-lake to over-land precipitation ratio in warm months (roughly 0.7 to 0.8 in June, July, and August) and a relatively high over-lake to overland precipitation ratio in cold months (roughly 1.3 to 1.4 in December and January), compared to gauge-based estimates. Our findings underscore a need to potentially update historical gauge-based precipitation estimates for large lake systems, including Lake Superior, and that RCMs appear to provide a robust and defensible basis for making those updates. Citation:

While the inverse relationship between antecedent snowpack in the Himalayas and Tibetan Plateau and subsequent monsoon rainfall in South and East Asia has been extensively studied and established, the potential for such a relationship between Rocky Mountain snowpack and the North American monsoon remains uncertain. The present study represents the first modeling assessment of this vital predictability issue, going beyond simple observational correlations, which fail to identify causality or a mechanism, by applying a regional climate model to demonstrate that a deep Rocky Mountain snowpack tends to hinder the poleward advance of the subtropical ridge and associated monsoon rainfall into the Southwest United States. A deep, extensive snowpack increases the surface albedo and provides an abundant surge of soil moisture, both of which reduce tropospheric temperatures in spring and early summer, weakening the land‐ocean thermal gradient and related monsoon system. This snow‐monsoon relationship, which may serve as a vital prediction tool of summer rainfall in the semi‐arid Southwest United States, has direct implications for regional water supply, streamflow, and biodiversity.

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