Validation of the Haines Index predicted from real-time high-resolution MM5 forecasts using rawinsonde observations over the eastern half of the USA
Hee-Jin In A and Shiyuan Zhong A BA Department of Geosciences, University of Houston, 312 S&R Building 1, 4800 Calhoun Rd, Houston, TX 77204, USA.
B Corresponding author. Telephone: +1 713 743 9130; fax: +1 713 748 7906; email: szhong@uh.edu
International Journal of Wildland Fire 14(3) 233-244 https://doi.org/10.1071/WF04056
Submitted: 1 October 2004 Accepted: 16 March 2005 Published: 12 September 2005
Abstract
The accuracy of the predicted Haines Index using the MM5 model is evaluated using rawinsonde observations. The evaluation compared predicted and observed Haines Indices during a 5-month period from 1 June to 31 October 2003 at 29 upper-air sounding sites within the modeling domain over much of the eastern half of the USA. Despite a consistent cold bias of 1–3°C in the lower to mid troposphere and a dry bias at the 850-mb and 700-mb levels in the MM5 results, little bias is found in the predicted Haines Index. This is because the temperature bias is largely cancelled in the calculation of the vertical temperature gradients used to derive the Haines Index and the dry bias is compensated by the slightly weaker instability in the model predictions. The predicted Haines Index captured the observed spatial and temporal variations of the observed index values resulting from changes in synoptic conditions. Of the 4184 total available soundings for the comparison, 45% had an exact match between the predicted and observed Haines Index categories and another 43% had a good match with the predicted and observed index differing by only one category. The rest of the 12% were cases where the predicted index fell under a category that was substantially different from the observed category, significantly raising or lowering the risk level for potentially dangerous fire behavior. Despite the general success, serious limitations exist when using the Haines Index derived from MM5 results for predicting high-risk conditions. This is because the prediction failed more than 50% of the time to capture the observed extreme cases when the observed index reached its highest possible value of 6. Although such extreme cases are rare, they represent conditions that are most conducive to dangerous and erratic fire behaviors and failure to predict these conditions may lead to serious consequences.
Additional keywords: fire management; fire weather forecasting; fire weather index.
Colle B, Westrick KJ , Mass CF (1999) Evaluation of MM5 and Eta-10 precipitation forecasts over the Pacific Northwest during the cool season. Weather Forecasting 14, 137–153.
| Crossref | GoogleScholarGoogle Scholar |
Haines DA (1988) A lower atmospheric severity index for wildland fires. National Weather Digest 13, 23–27.
![](../../media/share/OpenURL_Image.gif)
Janjic ZA (1990) The step-mountain coordinate: Physical package. Monthly Weather Review 118, 1429–1443.
| Crossref | GoogleScholarGoogle Scholar |
![](../../media/share/OpenURL_Image.gif)
Kain JS , Fritsch JM (1990) A one-dimensional entraining/detraining plume model and its application in convective parameterization. Journal of Atmospheric Sciences 47, 2784–2802.
| Crossref | GoogleScholarGoogle Scholar |
![](../../media/share/OpenURL_Image.gif)
Potter BE , Martin JE (2001) Accuracy of 24- and 48-hour forecasts of Haines’ Index. National Weather Digest 25, 38–46.
![](../../media/share/OpenURL_Image.gif)
Reisner JR, Rasmussen J , Bruintjes RT (1998) Explicit forecasting of supercooled liquid water in winter storms using the MM5 mesoscale model. Quarterly Journal of the Royal Meteorological Society 124, 1071–1107.
| Crossref | GoogleScholarGoogle Scholar |
![](../../media/share/OpenURL_Image.gif)
Werth P , Ochoa R (1993) The Haines Index and Idaho wildfire growth. Fire Management Notes 51(4), 9–13.
![](../../media/share/OpenURL_Image.gif)
Zhong S, In HJ, Bian X, Charney J, Heilman W , Potter B (2005) Evaluation of real-time high-resolution MM5 predictions over the Great Lakes Region. Weather and Forecasting 20, 63–81.
| Crossref |
![](../../media/share/OpenURL_Image.gif)