International Journal of Climatology

Bài báo này mô tả việc xây dựng một bộ dữ liệu khí hậu lưới cập nhật (được gọi là CRU TS3.10) từ các quan sát hàng tháng tại các trạm khí tượng trên khắp các vùng đất của thế giới. Các sai lệch tại trạm (so với trung bình giai đoạn 1961 đến 1990) được nội suy vào các ô lưới vĩ độ/kinh độ 0,5° bao phủ bề mặt đất toàn cầu (không bao gồm Antarctica), và được kết hợp với một khí hậu hiện có để nhận được các giá trị hàng tháng tuyệt đối. Bộ dữ liệu bao gồm sáu biến khí hậu chủ yếu độc lập (nhiệt độ trung bình, biên độ nhiệt độ ngày, lượng mưa, tần suất ngày ẩm, áp suất hơi và độ che phủ mây). Nhiệt độ tối đa và tối thiểu được suy ra một cách toán học từ các biến này. Các biến thứ cấp (tần suất ngày sương giá và bốc hơi tiềm năng) được ước lượng từ sáu biến chính bằng cách sử dụng các công thức nổi tiếng. Chuỗi thời gian cho các trung bình bán cầu và 20 khu vực quy mô bán châu lục lớn đã được tính toán (cho nhiệt độ trung bình, tối đa và tối thiểu cũng như tổng lượng mưa) và so sánh với một số sản phẩm lưới tương tự. Bộ dữ liệu mới có sự so sánh rất tích cực, với các sai lệch chính chủ yếu ở các vùng và/hoặc thời kỳ có ít dữ liệu quan sát hơn. CRU TS3.10 bao gồm các chẩn đoán liên quan đến từng giá trị nội suy cho biết số lượng trạm được sử dụng trong nội suy, cho phép xác định độ tin cậy của các giá trị một cách khách quan. Sản phẩm lưới này sẽ được cung cấp công khai, bao gồm cả chuỗi số liệu của các trạm đầu vào (http://www.cru.uea.ac.uk/ và http://badc.nerc.ac.uk/data/cru/). © 2013 Hiệp hội Khí tượng Hoàng gia

Throughout the tropics, population movements, urban growth, and industrialization are causing conditions that result in elevated temperatures within urban areas when compared with that in surrounding rural areas, a phenomenon known as the urban heat island (UHI). One such example is the city of San Juan, Puerto Rico. Our objective in this study was to quantify the UHI created by the San Juan Metropolitan Area over space and time using temperature data collected by mobile‐ and fixed‐station measurements. We also used the fixed‐station measurements to examine the relationship between average temperature at a given location and the density of remotely sensed vegetation located upwind. We then regressed temperatures against regional upwind land cover to predict future temperature with projected urbanization. Our data from the fixed stations show that the average nighttime UHI calculated between the urban reference and rural stations (ΔT_CBD–rural) was 2.15 °C during the usually wet season and 1.78 °C during the usually dry season. The maximum UHI value for San Juan was calculated as 4.7 °C between the urban and forest sites and 3.9 °C between the urban and an open, rural site. Comparisons of diurnal temperature trends at urban, grassland, and forested sites indicate that canopy cover reduced daytime warming. Temperature was predicted best (r² = 0.94) by vegetation in upwind easterly directions, especially that within 180 m of the sensor. Results from the mobile measurements show that the UHI has reached the base of the Luquillo Mountains. Predictions of future development and temperatures suggest that if the present pattern of development continues, over 140 km² of land that showed no signs of UHI in 2000 will have an average annual UHI between + 0.4 and + 1.55 °C by 2050. Furthermore, more than 130 km² of land area with a current UHI between + 0.4 and + 1.4 °C in 2000 will have an average UHI greater than + 1.55 °C by 2050. Copyright © 2010 Royal Meteorological Society

Chỉ số Lượng mưa Chuẩn hóa (SPI) được phát triển nhằm phát hiện hạn hán và các giai đoạn ẩm ướt theo nhiều thang thời gian khác nhau, một đặc điểm quan trọng mà các chỉ số hạn hán thông thường không thể mang lại. Ngày càng có nhiều người sử dụng SPI để giám sát hạn hán. Mặc dù việc tính toán SPI đơn giản hơn so với chỉ số hạn hán khác, như Chỉ số Hạn hán Palmer, nhưng vẫn còn khá phức tạp. Tại Trung Quốc, một chỉ số gọi là Chỉ số CZI của Trung Quốc đã được Trung tâm Khí hậu Quốc gia Trung Quốc sử dụng từ năm 1995 để giám sát điều kiện ẩm trên khắp cả nước. Việc tính toán chỉ số này dễ hơn so với SPI. Một chỉ số thứ ba, Điểm Z Thống kê, cũng có thể được sử dụng để giám sát hạn hán. Bài báo này đánh giá SPI, CZI và Điểm Z trên các thang thời gian là 1, 3, 6, 9 và 12 tháng, sử dụng tổng lượng mưa hàng tháng cho bốn địa điểm ở Trung Quốc từ tháng 1 năm 1951 đến tháng 12 năm 1998, đại diện cho các khí hậu ẩm và khô, cũng như các trường hợp hạn hán và lũ lụt. Các ưu điểm và khuyết điểm trong việc áp dụng mỗi chỉ số được so sánh. Kết quả nghiên cứu cho thấy rằng CZI và Điểm Z có thể cung cấp kết quả tương tự như SPI cho mọi thang thời gian, và rằng việc tính toán CZI và Điểm Z tương đối dễ so với SPI, có thể cung cấp các công cụ tốt hơn để giám sát điều kiện ẩm ướt. Bản quyền © 2001 Royal Meteorological Society.

Using satellite observations of Normalized Difference Vegetation Index together with climate data from other sources in a terrestrial biosphere model, inter‐annual variability of Net Primary Productivity (NPP) over India during 1981–2006 was studied. It is revealed that the variability is large over mixed shrub and grassland (MGL), moderate over cropland and small over the forest regions. Inter‐annual variability of NPP exhibits strong positive coherence with the variability of precipitation, and weak coherence with the variability of temperature and solar radiation. Estimated linear growth rate of annual NPP is 0.005 Pg C Yr⁻² which is equivalent to 8.5% over the country during past 25 years. This increase is primarily due to the enhancement of productivity over agricultural lands in the country. NPP has increased over most parts of the country during the early 15‐year period (1981–1995) resulting in a 10% growth rate of national NPP budget. On the other hand, the NPP growth rate has been reduced to 2.5% during later 15 years period (1991–2005) owing to large decline of NPP over the Indo‐Gangetic plains. Climate had a strong control on NPP growth rate during both the periods. Copyright © 2012 Royal Meteorological Society

The detrended fluctuation analysis (DFA) and multifractal DFA, which can detect nonstationarities of time series with trends, were applied to study long‐term persistence (LTP) and multifractal behaviour of 100 stations of daily precipitation and 145 stations of streamflow time series of Canada. Results show that all precipitation time series showed LTP at both small and large time scales, while streamflow time series generally showed nonstationary behaviour at small time scales and LTP at large time scales. The significant multifractal behaviour of Canadian precipitation and streamflow data can be accurately described by the universal multifractal model and the modified multiplicative cascade model. Precipitation over central Canada showed stronger multifractality than that of western and eastern Canada, while multifractality of streamflow data is less spatially homogeneous. The multifractal strength of precipitation is generally smaller than that of streamflow. Eleven (9) out of 100 precipitation stations showed positive (negative) temporal trends in parameters derived using the universal multifractal model, and about half of the stations whose streamflow data exhibited statistically significant abrupt change points showed a weakening or strengthening in the multifractal strength moving from the pre‐change to the post‐change periods. Differences in the multifractal strength between Canadian precipitation and streamflow data suggest that the persistence of streamflow was not only because streamflow is more autocorrelated than precipitation but also it is more consistently affected by human activities such as streamflow regulation.

Precipitation, temperature, and evaporative demand are the most dominant factors affecting water availability in a region. This study examines projected changes in these hydro‐climatic variables over western Canada under two greenhouse gas emissions scenarios using statistically downscaled, high resolution climate data generated by six Global Climate Models (GCMs) from the latest Coupled Model Intercomparison Project (CMIP5). Potential changes in the spatial and seasonal distributions of water availability over nine major western Canadian river basins are examined by computing the 3‐ and 12‐month standardized precipitation and evapotranspiration indices (SPEI‐3 and SPEI‐12). While individual GCM projections vary on the rate and seasonality of changes, they all indicate similar spatial and temporal patterns. The highest projected increases in precipitation and temperature are primarily in the northern basins, with some decreases in summer precipitation in the southern basins. The evolution of the SPEI‐12 values for the southern basins such as Columbia, Saskatchewan, Fraser and Athabasca indicate a gradual increase in the magnitude and duration of water deficit, while the reverse was found for most of the northern basins such as Peel/Lower Mackenzie, Liard, and Northern Pacific that show a gradual increase in water surplus on an annual basis. The SPEI‐3, however, shows that almost all river basins in western Canada, with the exception of Peel/Lower Mackenzie that are located in the extreme north of the study region, are projected to experience decreasing water availability in summer. In general, the study highlights the potential changes in the spatial and seasonal distribution of western Canadian water resources and sets the stage for a more detailed and process based hydro‐climate modelling study to be conducted in the region.

We present a dataset of daily resolution climatic time series that has been compiled for the European Climate Assessment (ECA). As of December 2001, this ECA dataset comprises 199 series of minimum, maximum and/or daily mean temperature and 195 series of daily precipitation amount observed at meteorological stations in Europe and the Middle East. Almost all series cover the standard normal period 1961–90, and about 50% extends back to at least 1925. Part of the dataset (90%) is made available for climate research on CDROM and through the Internet (at http://www.knmi.nl/samenw/eca).

A comparison of the ECA dataset with existing gridded datasets, having monthly resolution, shows that correlation coefficients between ECA stations and nearest land grid boxes between 1946 and 1999 are higher than 0.8 for 93% of the temperature series and for 51% of the precipitation series. The overall trends in the ECA dataset are of comparable magnitude to those in the gridded datasets.

The potential of the ECA dataset for climate studies is demonstrated in two examples. In the first example, it is shown that the winter (October–March) warming in Europe in the 1976–99 period is accompanied by a positive trend in the number of warm‐spell days at most stations, but not by a negative trend in the number of cold‐spell days. Instead, the number of cold‐spell days increases over Europe. In the second example, it is shown for winter precipitation between 1946 and 1999 that positive trends in the mean amount per wet day prevail in areas that are getting drier and wetter.

Because of its daily resolution, the ECA dataset enables a variety of empirical climate studies, including detailed analyses of changes in the occurrence of extremes in relation to changes in mean temperature and total precipitation. Copyright © 2002 Royal Meteorological Society.

A variation of a least squares regression approach to estimate missing daily maximum and minimum temperatures is developed and evaluated, specifically for temperature extremes. The method focuses on obtaining accurate estimates of annual exceedence counts (e.g. the number of days greater than or equal to the 90th percentile of daily maximum temperatures), as well as counts of consecutive exceedences, while limiting the estimation error associated with each individual value.

The performance of this method is compared with that of two existing methods developed for the entire temperature distribution. In these existing methods, temperature estimates are based on data from neighbouring stations using either regression or temperature departure‐based approaches.

Evaluation of our approach using cold minimum and warm maximum temperatures shows that the median percentage of correctly identified exceedence counts is 97% and the median percentage of correctly identified consecutive exceedence counts is 98%. The other existing methods tend to underestimate both single and consecutive exceedence counts. Using these procedures, the estimated exceedence counts are generally less than 80% of those that actually occurred.

Despite the fact that our method is tuned to estimate exceedence counts, the estimation accuracy of individual daily maximum or minimum temperatures is similar to that of the other estimation procedures. The median absolute error (MAE) using all temperatures greater than or equal to the 90th percentile (T₉₀)−1.1°C for ten climatically diverse stations is 1.28°C for our method, while the other methods give MAEs of 1.27 and 1.17°C. In terms of median error, however, the tendency for underprediction by the existing methods is pronounced with −0.77 and −0.61°C biases. Our optimized method is relatively unbiased as the resulting mean error is −0.12°C. Copyright © 2001 Royal Meteorological Society