One of the most commonly used metrics for both locating the Madden–Julian oscillation (MJO) geographically and defining the intensity of MJO convective activity is the real-time multivariate MJO (RMM) index. However, a climatology of the MJO, particularly with respect to the frequency of activity levels or of consecutive days at certain activity thresholds, does not yet exist. Thus, several climatological aspects of the MJO were developed in this study: 1) annual and 2) seasonal variability in MJO intensity, quantified using four defined activity categories (inactive, active, very active, and extremely active); 3) persistence in the above-defined four categories; 4) cycle length; and 5) low-frequency (decadal) variability. On an annual basis, MJO phases 1 and 2 occurred more often, and phase 8 occurred less often, than the other phases throughout the year. Notable seasonality was also found, particularly in the frequency of extremely active MJO in March–May (8% of days) compared with June–August (only 1% of days). The MJO was persistent in time and across intensity categories, and all activity categories the following day had at least an 80% chance of maintaining their amplitudes. Implications of this climatology are discussed, including length of complete MJO cycles (the shortest of which was 17 days) and correlations between MJO amplitude and atmospheric response.
This study details the creation of a gridded snowfall dataset for North America, with focus on the quality of the interpolated product. Daily snowfall amounts from National Weather Service Cooperative Observer Program stations and Meteorological Service of Canada surface stations are interpolated to 1° by 1° grids from 1900 to 2009 and examined for data record length and quality. The interpolation is validated spatially and temporally through the use of stratified sampling and k-fold cross-validation analyses. Interpolation errors average around 0.5 cm and range from less than 0.01 to greater than 2.5 cm. For most locations, this is within the measurement sensitivity. Grid cells with large variations in elevation experience higher errors and should be used with caution. A new gridded snowfall climatology is presented based on in situ observations that capture seasonal and interannual variability in monthly snowfall over most of the North American land area from 1949 to 2009. The Community Collaborative Rain, Hail and Snow Network is used as an independent set of point data that is compared to the gridded product. Errors are mainly in the form of the gridded data underestimating snowfall compared to the point data. The spatial extent, temporal length, and resolution of the dataset are unprecedented with regard to observational snowfall products and will present new opportunities for examining snowfall across North America.
Radiative fluxes are critical for understanding the energy budget of the Arctic region, where the climate has been changing rapidly and is projected to continue to change. This work investigates causes of present-day biases and future projections of top-of-atmosphere (TOA) Arctic radiative fluxes in phase 5 of the Coupled Model Intercomparison Project (CMIP5). Compared to Clouds and the Earth's Radiant Energy System Energy Balanced and Filled (CERES-EBAF), CMIP5 net TOA downward shortwave (SW) flux biases are larger than outgoing longwave radiation (OLR) biases. The primary contributions to modeled TOA SW flux biases are biases in cloud amount and snow cover extent compared to the GCM-Oriented CALIPSO Cloud Product (CALIPSO-GOCCP) and the newly developed Making Earth System Data Records for Use in Research Environments (MEaSUREs) dataset, respectively (with most models predicting insufficient cloud amount and snow cover in the Arctic), and biases with sea ice albedo. Future projections (2081-90) with representative concentration pathway 8.5 (RCP8.5) simulations suggest increasing net TOA downward SW fluxes (18 W m 22 ) over the Arctic basin due to a decrease of surface albedo from melting snow and ice, and increasing OLR (16 W m 22 ) due to an increase in surface temperatures. The largest contribution to future Arctic net TOA downward SW flux increases is declining sea ice area, followed by declining snow cover area on land, reductions to sea ice albedo, and reductions to snow albedo on land. Cloud amount is not projected to change significantly. These results suggest the importance of accurately representing both the surface area and albedos of sea ice and snow cover as well as cloud amount in order to accurately represent TOA radiative fluxes for the present-day climate and future projections.
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