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S. Rabenhorst, D. N. Whiteman, D.-L. Zhang, and B. Demoz

Abstract

The Water Vapor Variability-Satellite/Sondes (WAVES) 2006 field campaign provided a contiguous 5-day period of concentrated high-resolution measurements to examine finescale boundary layer phenomena under the influence of a summertime subtropical high over the mid-Atlantic region that is characterized by complex geography. A holistic analytical approach to low-level wind observations was adopted to identify the low-level flow structures and patterns of evolution on the basis of airmass properties and origination. An analysis of the measurements and the other available observations is consistent with the classic depiction of the daytime boundary layer development but revealed a pronounced diurnal cycle that was categorized into three stages: (i) daytime growth of the convective boundary layer, (ii) flow intensification into a low-level jet regime after dusk, and (iii) interruption by a downslope wind regime after midnight. The use of the field campaign data allows for the differentiation of the latter two flow regimes by their directions with respect to the orientation of the Appalachian Mountains and their airmass origins. Previous studies that have investigated mountain flows and low-level jet circulations have focused on regions with overt geographic prominence, stark gradients, or frequent reoccurrences, whereby such meteorological phenomena exhibit a clear signature and can be easily isolated and diagnosed. The results of this study provide evidence that similar circulation patterns operate in nonclassic locations with milder topography and atmospheric gradients, such as the mid-Atlantic region. The new results have important implications for the understanding of the mountain-forced flows and some air quality problems during the nocturnal period.

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L. Borowska, D. Zrnić, A. Ryzhkov, P. Zhang, and C. Simmer

Abstract

The authors evaluate rainfall estimates from the new polarimetric X-band radar at Bonn, Germany, for a period between mid-November and the end of December 2009 by comparison with rain gauges. The emphasis is on slightly more than 1-month accumulations over areas minimally affected by beam blockage. The rain regime was characterized by reflectivities mainly below 45 dBZ, maximum observed rain rates of 47 mm h−1, a mean rain rate of 0.1 mm h−1, and brightband altitudes between 0.6 and 2.4 km above the ground. Both the reflectivity factor and the specific differential phase are used to obtain the rain rates. The accuracy of rain total estimates is evaluated from the statistics of the differences between radar and rain gauge measurements. Polarimetry provides improvement in the statistics of reflectivity-based measurements by reducing the bias and RMS errors from −25% to 7% and from 33% to 17%, respectively. Essential to this improvement is separation of the data into those attributed to pure rain, those from the bright band, and those due to nonmeteorological scatterers. A type-specific (rain or wet snow) relation is applied to obtain the rain rate by matching on the average the contribution by wet snow to the radar-measured rainfall below the bright band. The measurement of rain using specific differential phase is the most robust and can be applied to the very low rain rates and still produce credible accumulation estimates characterized with a standard deviation of 11% but a bias of −25%. A composite estimator is also tested and discussed.

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T. Zhang, T. Scambos, T. Haran, L. D. Hinzman, Roger G. Barry, and D. L. Kane

Abstract

Spatial and temporal variations of surface albedo on the North Slope of Alaska were investigated using both ground-based tower measurements and satellite remote sensing data. Ground-based measurements of incident and reflected solar radiation at several stations along the Dalton Highway over the period 1985–98 are used to determine in situ surface albedo. Advanced Very High Resolution Radiometer (AVHRR)-derived surface albedo were obtained from AVHRR Polar Pathfinder products, available from the National Snow and Ice Data Center, using a modified cloud mask. AVHRR-derived surface albedo agrees closely with in situ measurements. Results from this study indicate that surface albedo varies from greater than 0.9 for a snow-covered land surface under overcast conditions to less than 0.1 for a wet tundra land surface. Five distinct temporal periods are discerned, based on seasonal variations of surface albedo: winter stationary, spring snowmelt, postsnowmelt, summer stationary, and autumn freeze-up periods. Spatially, the North Slope is divided into three zones based on patterns of seasonal variation in surface albedo. A mountain zone is along the ranges and slopes of the Brooks Range, with elevations above 1000 m. When compared with the other two zones, surface albedo in this zone is the lowest in winter, varying from 0.4 to 0.7, and relatively high in summer, from 0.15 to 0.2. The foothills zone is along the foothills of the Brooks Range, with elevations from 300 to 1000 m. Surface albedo is relatively high in this zone in winter (0.8) and the highest in summer (0.2). Surface albedo in this zone changes very rapidly from 0.8 to 0.2 within a couple of weeks in spring. The coastal zone is along the Arctic coastal plain, with elevations lower than 300 m. Coastal zone surface albedo is the highest in winter (>0.8) and the lowest in summer (<0.15). This study suggests that the heat island effect in the vicinity of Barrow, Alaska, is very minimal. Progressive earlier snow cover disappearance at the Barrow National Weather Service station may be an indication of regional spring warming. This study also suggests that snow surface albedo in land surface models should be treated differently for snow at high latitudes as compared with snow in midlatitudes, especially during winter months.

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B. R. Bonsal, X. Zhang, L. A. Vincent, and W. D. Hogg

Abstract

Recent studies have shown that, since 1900, mean annual temperature over southern Canada has increased by an average of 0.9°C, with the largest warming during winter and early spring. Every season was associated with greater increases in minimum temperature as opposed to maximum, thus resulting in a significant decrease in the daily temperature range (DTR). The second half of the twentieth century was associated with significant winter and spring warming in the south and west, and cooling in the northeast. However, no significant changes in DTR were observed during this period. This investigation goes beyond the annual/seasonal scales by examining trends and variability in daily minimum and maximum temperature with particular emphasis on extremes. Using recently updated, homogenized daily data, spatial and temporal characteristics of daily and extreme temperature-related variables are analyzed on a seasonal basis for the periods of 1900–98 (southern Canada), and 1950–98 (the entire country). From 1900 to 1998, the majority of southern Canada shows significantly increasing trends to the lower and higher percentiles of the daily minimum and maximum temperature distribution. The findings translate into fewer days with extreme low temperature during winter, spring, and summer and more days with extreme high temperature during winter and spring. No consistent trends are found for the higher percentiles of summer daily maximum temperature, indicating little change to the number of extreme hot summer days. Over the southwest, increases are larger to the left-hand side of the daily minimum and maximum temperature distribution, resulting in significant decreases to the intraseasonal standard deviation of daily temperature. The 1950–98 results are somewhat different from the entire century, especially, during winter and spring. This result includes significant increases to the low and high percentiles over the west, and decreases over the east. This analysis reveals that the largest individual daily temperature trends (both minimum and maximum) occur during winter and early spring, when substantial warming is observed. For summer, increases are only associated with daily minimum temperature. Autumn displays varying results, with some late season cooling, mainly over western regions. The observed warming trends have a substantial effect on several economically sensitive indices. This effect includes significant increases in the number of growing and cooling degree days and significant decreases in heating degree days. In addition, the length of the frost-free period is significantly longer over most of the country.

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I. V. Polyakov, U. S. Bhatt, H. L. Simmons, D. Walsh, J. E. Walsh, and X. Zhang

Abstract

Substantial changes occurred in the North Atlantic during the twentieth century. Here the authors demonstrate, through the analysis of a vast collection of observational data, that multidecadal fluctuations on time scales of 50–80 yr are prevalent in the upper 3000 m of the North Atlantic Ocean. Spatially averaged temperature and salinity from the 0–300- and 1000–3000-m layers vary in opposition: prolonged periods of cooling and freshening (warming and salinification) in one layer are generally associated with opposite tendencies in the other layer, consistent with the notion of thermohaline overturning circulation. In the 1990s, widespread cooling and freshening was a dominant feature in the 1000–3000-m layer, whereas warming and salinification generally dominated in the upper 300 m, except for the subpolar North Atlantic where complex exchanges with the Arctic Ocean occur. The single-signed basin-scale pattern of multidecadal variability is evident from decadal 1000–3000-m temperature and salinity fields, whereas upper-ocean temperature and salinity distributions have a more complicated spatial pattern. Results suggest a general warming trend of 0.012° ± 0.009°C decade−1 in the upper-3000-m North Atlantic over the last 55 yr of the twentieth century, although during this time there are periods in which short-term trends are strongly amplified by multidecadal variability. Since warming (cooling) is generally associated with salinification (freshening) for these large-scale fluctuations, qualitatively tracking the mean temperature–salinity relationship, vertical displacement of isotherms appears to play an important role in this warming and in other observed fluctuations. Finally, since the North Atlantic Ocean plays a crucial role in establishing and regulating global thermohaline circulation, the multidecadal fluctuations of the heat and freshwater balance discussed here should be considered when assessing long-term climate change and variability, both in the North Atlantic and at global scales.

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Gan Zhang, Hiroyuki Murakami, Xiaosong Yang, Kirsten L. Findell, Andrew T. Wittenberg, and Liwei Jia

Abstract

Climate models often show errors in simulating and predicting tropical cyclone (TC) activity, but the sources of these errors are not well understood. This study proposes an evaluation framework and analyzes three sets of experiments conducted using a seasonal prediction model developed at the Geophysical Fluid Dynamics Laboratory (GFDL). These experiments apply the nudging technique to the model integration and/or initialization to estimate possible improvements from nearly perfect model conditions. The results suggest that reducing sea surface temperature (SST) errors remains important for better predicting TC activity at long forecast leads—even in a flux-adjusted model with reduced climatological biases. Other error sources also contribute to biases in simulated TC activity, with notable manifestations on regional scales. A novel finding is that the coupling and initialization of the land and atmosphere components can affect seasonal TC prediction skill. Simulated year-to-year variations in June land conditions over North America show a significant lead correlation with the North Atlantic large-scale environment and TC activity. Improved land–atmosphere initialization appears to improve the Atlantic TC predictions initialized in some summer months. For short-lead predictions initialized in June, the potential skill improvements attributable to land–atmosphere initialization might be comparable to those achievable with perfect SST predictions. Overall, this study delineates the SST and non-oceanic error sources in predicting TC activity and highlights avenues for improving predictions. The nudging-based evaluation framework can be applied to other models and help improve predictions of other weather extremes.

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Ruanyu Zhang, Christian D. Kummerow, David L. Randel, Paula J. Brown, Wesley Berg, and Zhenzhan Wang

Abstract

This study focuses on the tropical cyclone rainfall retrieval using FY-3B Microwave Radiation Imager (MWRI) brightness temperatures (Tbs). The GPROF, a fully parametric approach based on the Bayesian scheme, is adapted for use by the MWRI sensor. The MWRI GPROF algorithm is an ocean-only scheme used to estimate rain rates and hydrometeor vertical profiles. An a priori database is constructed from MWRI simulated Tbs, the GPM Microwave Imager (GMI) and Dual-Frequency Precipitation Radar (DPR) combined data, and ancillary data resulting in about 100 000 rainfall profiles. The performance of MWRI retrievals is consistent with DPR observations, even though MWRI retrievals slightly overestimate low rain rates and underestimate high rain rates. The total bias of MWRI retrievals is less than 13% of the mean rain rate of DPR precipitation. Statistical comparisons over GMI GPROF, GMI Hurricane GPROF (HGPROF), and MWRI GPROF retrievals show MWRI GPROF retrievals are consistent in terms of spatial distribution and rain estimates for TCs compared with the other two estimates. In terms of the global precipitation, the mean rain rates at different distances from best track locations for five TC categories are used to identify substantial differences between mean MWRI and GMI GPROF retrievals. After correcting the biases between MWRI and GMI retrievals, the performance of MWRI retrievals shows slight overestimate for light rain rates while underestimating rain rates near the eyewall for category 4 and 5 only.

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L. A. Vincent, X. Zhang, R. D. Brown, Y. Feng, E. Mekis, E. J. Milewska, H. Wan, and X. L. Wang

Abstract

Trends in Canada’s climate are analyzed using recently updated data to provide a comprehensive view of climate variability and long-term changes over the period of instrumental record. Trends in surface air temperature, precipitation, snow cover, and streamflow indices are examined along with the potential impact of low-frequency variability related to large-scale atmospheric and oceanic oscillations on these trends. The results show that temperature has increased significantly in most regions of Canada over the period 1948–2012, with the largest warming occurring in winter and spring. Precipitation has also increased, especially in the north. Changes in other climate and hydroclimatic variables, including a decrease in the amount of precipitation falling as snow in the south, fewer days with snow cover, an earlier start of the spring high-flow season, and an increase in April streamflow, are consistent with the observed warming and precipitation trends. For the period 1900–2012, there are sufficient temperature and precipitation data for trend analysis for southern Canada (south of 60°N) only. During this period, temperature has increased significantly across the region, precipitation has increased, and the amount of precipitation falling as snow has decreased in many areas south of 55°N. The results also show that modes of low-frequency variability modulate the spatial distribution and strength of the trends; however, they alone cannot explain the observed long-term trends in these climate variables.

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P.J. Sellers, D.A. Randall, G.J. Collatz, J.A. Berry, C.B. Field, D.A. Dazlich, C. Zhang, G.D. Collelo, and L. Bounoua

Abstract

The formulation of a revised land surface parameterization for use within atmospheric general circulation models (GCMs) is presented. The model (SiB2) incorporates several significant improvements over the first version of the Simple Biosphere model (SiB) described in Sellers et al. The improvements can be summarized as follows:

(i) incorporation of a realistic canopy photosynthesis–conductance model to describe the simultaneous transfer of CO2 and water vapor into and out of the vegetation, respectively;

(ii) use of satellite data, as described in a companion paper, Part II, to describe the vegetation phonology;

(iii) modification of the hydrological submodel to give better descriptions of baseflows and a more reliable calculation of interlayer exchanges within the soil profile;

(iv) incorporation of a “patchy” snowmelt treatment, which prevents rapid thermal and surface reflectance transitions when the area-averaged snow cover is low and decreasing.

To accommodate the changes in (i) and (ii) above, the original two-layer vegetation canopy structure of SiB2 has been reduced to a single layer in SiB2. The use of satellite data in SiB2 and the performance of SiB2 when coupled to a GCM are described in the two companion papers, Part II and III.

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Peter A. Bieniek, Uma S. Bhatt, Larry A. Rundquist, Scott D. Lindsey, Xiangdong Zhang, and Richard L. Thoman

Abstract

Frozen rivers in the Arctic serve as critical highways because of the lack of roads; therefore, it is important to understand the key mechanisms that control the timing of river ice breakup. The relationships between springtime Interior Alaska river ice breakup date and the large-scale climate are investigated for the Yukon, Tanana, Kuskokwim, and Chena Rivers for the 1949–2008 period. The most important climate factor that determines breakup is April–May surface air temperatures (SATs). Breakup tends to occur earlier when Alaska April–May SATs and river flow are above normal. Spring SATs are influenced by storms approaching the state from the Gulf of Alaska, which are part of large-scale climate anomalies that compare favorably with ENSO. During the warm phase of ENSO fewer storms travel into the Gulf of Alaska during the spring, resulting in a decrease of cloud cover over Alaska, which increases surface solar insolation. This results in warmer-than-average springtime SATs and an earlier breakup date. The opposite holds true for the cold phase of ENSO. Increased wintertime precipitation over Alaska has a secondary impact on earlier breakup by increasing spring river discharge. Improved springtime Alaska temperature predictions would enhance the ability to forecast the timing of river ice breakup.

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