Simulated data from Kelly et al. 2011, A signal-to-noise index to quantify the potential for peak detection in sediment-charcoal records, Quaternary Reserach, 75: 11-17.

Simulated charcoal time series used in: Kelly, R. F., Higuera, P. E., Barrett, C. M. &amp; Hu, F. S. (2011) A signal-to-noise index to quantify the potential for peak detection in sediment-charcoal records. Quaternary Research, 75, 11-17. Each .csv file contains "summary data" that describes the parameters used in the <em>CharAnalysis</em> program for threshold determination. Row 16 includes column headings for CharAnalysis input, as follows: age -- [yr BP] age of simulated record cm -- [cm] depth of simulated record count -- [#] charcoal count (not discrete) vol -- [cm3] volume of sample acc -- [# cm^-2 yr^-1] Charcoal accumulation rate bkg -- [# cm^-2 yr^-1] Background charcoal rsd -- [# cm^-2 yr^-1] Residual charcoal thr -- [# cm^-2 yr^-1] Threshold separating peaks from non-peak values pkBool -- [binary] Peaks (1) or non-peak values (0) pkMCP -- [binary] Equals 1 if a "peak" value was screened out by the minimum count test. That is, the sample surpassed the threshold, but the count was low enough to not pass the minimum count test. (These values should almost always be 0) sni -- [index] Signal-to-noise index sniSm -- [index] Smoothd SNI Detials from Kelly et al. (2011): "Simulated records were generated using the CharSim model (Higuera et al., 2007), which simulates a spatially and temporally explicit fire regime, charcoal production and dispersal processes, primary (airborne) and secondary (slope wash and withinlake redeposition) deposition, sediment mixing, and sediment sampling. The <strong>CS1</strong> scenario is based on model parameters representing boreal-forest charcoal records, with high temporal resolution (15-yr contiguous samples) and little vertical mixing in sediments. The <strong>CS2</strong> scenario differs from CS1 only in that additional sediment mixing is simulated (vertical mixing depth doubled from 1.0 to 2.0 cm), as might be observed in shallower lakes. In both CS1 and CS2 scenarios, fire sizes mimic those observed in Alaska from 1988 to 2003 (Alaska Fire Service, 2004). By contrast, the <strong>CS3</strong> scenario is based on fires of constant size, equal to the mean fire size of the same dataset. This scenario creates a charcoal series with a relatively uniform distribution of CHAR values, and illustrates a record in which peaks from local fires are difficult to detect due to processes independent of charcoal taphonomy."

本数据集为用于以下研究的模拟炭屑时间序列：Kelly, R. F., Higuera, P. E., Barrett, C. M. & Hu, F. S. (2011) 《用于量化沉积物炭屑记录中峰检测潜力的信噪比指数（signal-to-noise index）》，《第四纪研究》(Quaternary Research)，75卷，11-17页。每个.csv文件均包含用于<em>炭屑分析程序（CharAnalysis）</em>阈值确定的参数汇总数据。第16行为<em>炭屑分析程序（CharAnalysis）</em>的输入列标题，各列含义如下：
age -- [yr BP]：年代——[距今年份（yr BP）]
cm -- [cm]：样品深度——[单位：cm]
count -- [#]：炭屑计数——[单位：个（#），非离散计数]
vol -- [cm³]：样品体积——[单位：cm³]
acc -- [# cm⁻² yr⁻¹]：炭屑堆积速率——[单位：# cm⁻² yr⁻¹]
bkg -- [# cm⁻² yr⁻¹]：背景炭屑浓度——[单位：# cm⁻² yr⁻¹]
rsd -- [# cm⁻² yr⁻¹]：残余炭屑浓度——[单位：# cm⁻² yr⁻¹]
thr -- [# cm⁻² yr⁻¹]：阈值——[单位：# cm⁻² yr⁻¹]，用于区分峰值与非峰值
pkBool -- [binary]：峰值标识——[二进制格式，峰值记为1，非峰值记为0]
pkMCP -- [binary]：最小计数测试筛除标识——[二进制格式，若某“峰”值因未通过最小计数测试被筛除则记为1。即该样品超过阈值，但炭屑计数过低未满足最小计数要求，此类值通常应为0]
sni -- [index]：信噪比指数（signal-to-noise index）——[索引值]
sniSm -- [index]：平滑化信噪比指数——[索引值]

据Kelly等人(2011)的研究描述：“模拟记录通过<em>CharSim模型（CharSim）</em>生成，该模型可模拟时空显性的火灾动态、炭屑产生与扩散过程、一次（大气沉降）和二次（坡面冲刷与湖内再沉积）沉积作用、沉积物混合以及沉积物采样流程。<strong>CS1</strong>情景基于代表北方林带炭屑记录的模型参数，具备高时间分辨率（15年连续采样）且沉积物垂向混合极弱。<strong>CS2</strong>情景仅与CS1存在一处差异：增加了沉积物混合模拟（垂向混合深度从1.0cm增至2.0cm），该情况常见于较浅湖泊。在CS1与CS2两种情景中，火灾规模均参照1988至2003年阿拉斯加观测到的火灾规模（阿拉斯加消防局，2004）。与之相对，<strong>CS3</strong>情景采用恒定规模的火灾，其规模等于前述数据集的平均火灾规模。该情景生成的炭屑序列的炭屑值分布相对均匀，展现了一类因非炭屑埋藏学过程导致本地火灾峰难以识别的记录。”